AAAI Publications, The Thirtieth International Flairs Conference

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Recommending from Experience
Francisco J. Peña, Derek Bridge

Last modified: 2017-05-08

Abstract


In this paper we present RC, a context-driven recommender system that mines contextual information from user-generated reviews and makes recommendations based on the users' experiences. RC mines the contextual information from the user-generated reviews using a form of topic modeling. This means that, unlike other context-aware recommender systems, RC does not have a predefined set of contextual variables. After mining the contextual information, RC makes top-n recommendations using a Factorization Machine with the contextual topics as side information. Our experiments on two datasets of ratings and reviews show that RC has higher recall than a conventional recommender.

Keywords


recommender systems; topic modelling; context-aware recommendations

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